Metadata-Version: 1.1
Name: pandana
Version: 0.4.2
Summary: Pandas Network Analysis - dataframes of network queries, quickly
Home-page: https://udst.github.io/pandana/
Author: UrbanSim Inc.
Author-email: UNKNOWN
License: AGPL
Description: [![Build Status](https://travis-ci.org/UDST/pandana.svg?branch=master)](https://travis-ci.org/UDST/pandana)
        [![Coverage Status](https://coveralls.io/repos/github/UDST/pandana/badge.svg?branch=master)](https://coveralls.io/github/UDST/pandana?branch=master)
        
        # Pandana
        
        Pandana is a Python package that uses [contraction hierarchies](https://en.wikipedia.org/wiki/Contraction_hierarchies) to perform rapid network calculations including shortest paths and accessibility buffers. The computations are parallelized for use on multi-core machines using an underlying C/C++ library. Pandana is tested on Mac, Linux, and Windows with Python 2.7, 3.6, and 3.7.
        
        Documentation: http://udst.github.io/pandana
        
        
        ### Installation
        
        The easiest way to install Pandana is using the [Anaconda](https://www.anaconda.com/distribution/) package manager. Pandana's Anaconda distributions are pre-compiled and include multi-threading support on all platforms. 
        
        `conda install pandana --channel conda-forge`
        
        See the documentation for information about other [installation options](http://udst.github.io/pandana/installation.html).
        
        
        ### Demo
        
        [Example.ipynb](https://github.com/UDST/pandana/blob/master/examples/Example.ipynb)
        
        The image below shows the distance to the _second_ nearest restaurant from each street intersection in the city of San Francisco. Pandana can calculate this in about half a second of computation time. 
        
        <img src="https://raw.githubusercontent.com/udst/pandana/master/docs/img/distance_to_restaurants.png" width=400>
        
        
        ## Acknowledgments
        
        None of this would be possible without the help of Dennis Luxen and
        his [OSRM](https://github.com/DennisOSRM/Project-OSRM) project. Thank you Dennis!
        
        
        ### Academic Literature
        
        A [complete description of the
        methodology](http://onlinepubs.trb.org/onlinepubs/conferences/2012/4thITM/Papers-A/0117-000062.pdf)
        was presented at the Transportation Research Board Annual Conference in 2012. Please cite this paper when referring
        to the methodology implemented by this library.
        
        
        ### Related UDST libraries
        
        - [OSMnet](https://github.com/udst/osmnet)
        - [UrbanAccess](https://github.com/udst/urbanaccess)
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
